CFD techniques for mixing and dispersion of desalination ... · April 2014 CFD techniques for...

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April 2014 CFD techniques for mixing and dispersion of desalination and other marine discharges ICDEMOS, Muscat, Sultanate of Oman, 2014 David Robinson, Matthew Wood, Matthew Piggott & Gerard Gorman

Transcript of CFD techniques for mixing and dispersion of desalination ... · April 2014 CFD techniques for...

April 2014

CFD techniques for mixing and dispersion of desalination and other marine discharges

ICDEMOS, Muscat, Sultanate of Oman, 2014

David Robinson, Matthew Wood, Matthew Piggott & Gerard Gorman

© HR Wallingford 2014

Content

Background and motivation CFD: a tool for dispersion modelling Preliminary results Planned work

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© HR Wallingford 2014

Motivation

Desal / IWPP discharge plumes Benthic thermal-saline impact Dispersion prediction is vital for: EIA Engineering studies (outfall design, recirculation)

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© HR Wallingford 2014

HR Wallingford in Oman

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Far-field dispersion

Model coupling

Near-field dilution

(mixing zone)

Dispersion modelling approaches

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Validated procedure

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Coupled studies are common

HR Wallingford framework: “Dense Jet Assessment Procedure”, Wood & Mead (2008)

Validated against newly available mid-/far-field data: “Validation of computational models for hypersaline and other dense marine discharges”, Wood et al, (2014)

© HR Wallingford 2014

Benefits & drawbacks

Benefits: Methods generally work well for smaller discharges:

Simple exchanges of mass & momentum Relatively quick to implement

Drawbacks Plume interactions / neighbouring facilities :

2-way exchange of pollutant concentrations is challenging

Potential solution: CFD Computing power increases Adaptive meshing techniques Seamless coverage of the entire domain

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Barka

Sohar

© HR Wallingford 2014

CFD

History – near-field Fluidity:

Open-source, developed by Imperial Navier-Stokes on 3D unstructured meshes Discretisation: Finite element & control volume Mesh adaptivity

Key differentiator – multi-scale:

3D CFD model + efficient coastal flow modelling system

Used to simulate ocean and tidal flows

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PhD research

Long-term goals: Extend Fluidity’s multi-scale capabilities a fully integrated CFD hydrodynamic & pollutant dispersion model

First stage: Explore near-field abilities

Horizontal buoyant jet Angled dense jet

Compared predictions with published laboratory data, or validated integral models.

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Near-field test cases

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Parameter Horizontal buoyant jet Angled dense jet

Inlet diameter (mm) 9.4 3.3 Densimetric Froude number, F 10.7 21.3 Reynolds number 6000 2500 References for comparison CorJet integral model Experimental data

Parameters for comparison • Centreline trajectory • Mean axial velocity decay

• Centreline terminal rise height • Bottom impact distance • Minimum impact dilution

Zt

Si Xi

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Numerical methods

Unstructured tetrahedral elements Turbulence:

k-ε V-LES

Adaptive time-stepping and meshing

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Horizontal buoyant jet

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Horizontal buoyant jet

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Centreline trajectory

Centreline velocity decay

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Angled dense jet

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Angled dense jet

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k1 = zt/dF k2 = xi/dF k3 = Si/F Zeitoun et al. (1972) - 3.19 1.12 Roberts et al. (1997) - 2.4 1.6 +/- 0.12 Nemlioglu & Roberts (2006) - 3.25 1.7 Cipollina et al. (2005) 1.77 2.25 - Kikkert et al. (2007) 1.6 2.72 1.81 Papakonstantis et al. (2011a and 2011b) 1.68 2.75 1.68 +/- 0.1

Terminal rise

height

Impact distance

Impact dilution

© HR Wallingford 2014

Summary

HR Wallingford uses a validated coupled modelling procedure involving Hydrodynamic models Near-field models

Future will involve more CFD

Preliminary work with Imperial College is encouraging:

Buoyant jet compares well (trajectories and dilutions) Dense case requires mesh refinement

Next steps of PhD: Adapt mesh to far-field Range of ambient currents Multiport diffusers

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© HR Wallingford 2014

Thank you!

Matthew Wood Principal Scientist HR Wallingford [email protected]

David Robinson Imperial College London [email protected]

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